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Henry_B_Intel
Employee
67 Views

Looking for optimized sliding window helper functions

I have not been able to find any optimized sliding window helper functions. As an example, I'd like to run a filter over 128accelermeter samples. On the next iteration, I'd to add 4 new samples and remove the 4 oldset samples (i.e. standard sliding window behavior). What is the optimal way of doing this?
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Chao_Y_Intel
Employee
67 Views

I have not been able to find any optimized sliding window helper functions. As an example, I'd like to run a filter over 128accelermeter samples. On the next iteration, I'd to add 4 new samples and remove the 4 oldset samples (i.e. standard sliding window behavior). What is the optimal way of doing this?



Hi,

See some comment from the expert:

It is not clear what kind of filter the code wants to apply, If it is simple FIR, please check FIR MR with corresponding up/down Factors.

Thanks,
Chao
67 Views

Quoting - Chao Y (Intel)



Hi,

See some comment from the expert:

It is not clear what kind of filter the code wants to apply, If it is simple FIR, please check FIR MR with corresponding up/down Factors.

Thanks,
Chao

Ivan_Ryzhachkin__Int
New Contributor I
67 Views

I have not been able to find any optimized sliding window helper functions. As an example, I'd like to run a filter over 128accelermeter samples. On the next iteration, I'd to add 4 new samples and remove the 4 oldset samples (i.e. standard sliding window behavior). What is the optimal way of doing this?

Hi Henry,
to perform sliding windowing would suggest ~ the folowing IPP code:

ippsMove_32f(&buf[FRAME_SIZE], buf, WINDOW_LEN - FRAME_SIZE);
ippsZero_32f(&buf[WINDOW_LEN - FRAME_SIZE], FRAME_SIZE);
ippsMove_32f(&sBuf[FRAME_SIZE], sBuf, WINDOW_LEN - FRAME_SIZE);
ippsCopy_32f(pSrcDst,&sBuf[WINDOW_LEN - FRAME_SIZE], FRAME_SIZE);
ippsAddProduct_32f(&sBuf[0],window,buf,WINDOW_LEN);
regards,
Ivan

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